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Emperical Interference

Haptic Intelligence

Modern Magnetic Systems

Perceiving Systems

Physical Intelligence

Robotic Materials

Social Foundations of Computation


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Autonomous Vision

Autonomous Learning

Bioinspired Autonomous Miniature Robots

Dynamic Locomotion

Embodied Vision

Human Aspects of Machine Learning

Intelligent Control Systems

Learning and Dynamical Systems

Locomotion in Biorobotic and Somatic Systems

Micro, Nano, and Molecular Systems

Movement Generation and Control

Neural Capture and Synthesis

Physics for Inference and Optimization

Organizational Leadership and Diversity

Probabilistic Learning Group


Topics

Robot Learning

Conference Paper

2022

Autonomous Learning

Robotics

AI

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Empirical Inference Conference Paper Moûsai: Efficient Text-to-Music Diffusion Models Schneider, F., Kamal, O., Jin, Z., Schölkopf, B. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL), Volume 1: Long Papers:8050-8068, (Editors: Lun-Wei Ku and Andre Martins and Vivek Srikumar), Association for Computational Linguistics, August 2024 (Published) URL BibTeX

Empirical Inference Conference Paper CausalCite: A Causal Formulation of Paper Citations Agrawal, I., Jin, Z., Mokhtarian, E., Guo, S., Chen, Y., Sachan, M., Schölkopf, B. Findings of the Association for Computational Linguistics (ACL), 8395-8410, (Editors: Ku, Lun-Wei and Martins, Andre and Srikumar, Vivek), Association for Computational Linguistics, August 2024 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper A Sparsity Principle for Partially Observable Causal Representation Learning Xu, D., Yao, D., Lachapelle, S., Taslakian, P., von Kügelgen, J., Locatello, F., Magliacane, S. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:55389-55433, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) URL BibTeX

Empirical Inference Conference Paper Accuracy on the wrong line: On the pitfalls of noisy data for OOD generalisation Sanyal, A., Hu, Y., Yu, Y., Ma, Y., Wang, Y., Schölkopf, B. ICML 2024 Next Generation of AI Safety Workshop (Oral), July 2024 (Published) arXiv PDF BibTeX

Empirical Inference Conference Paper All-in-one simulation-based inference Gloeckler, M., Deistler, M., Weilbach, C. D., Wood, F., Macke, J. H. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:15735-15766, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) URL BibTeX

Learning and Dynamical Systems Empirical Inference Article Deep Backtracking Counterfactuals for Causally Compliant Explanations Kladny, K., Kügelgen, J. V., Schölkopf, B., Muehlebach, M. Transactions on Machine Learning Research, July 2024 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Detecting and Identifying Selection Structure in Sequential Data Zheng, Y., Tang, Z., Qiu, Y., Schölkopf, B., Zhang, K. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:61498-61525, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) URL BibTeX

Empirical Inference Conference Paper Diffusion Tempering Improves Parameter Estimation with Probabilistic Integrators for ODEs Beck, J., Bosch, N., Deistler, M., Kadhim, K. L., Macke, J. H., Hennig, P., Berens, P. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:3305-3326, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Diffusive Gibbs Sampling Chen*, W., Zhang*, M., Paige, B., Hernández-Lobato, J. M., Barber, D. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:7731-7747, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners? Opedal, A., Stolfo, A., Shirakami, H., Jiao, Y., Cotterell, R., Schölkopf, B., Saparov, A., Sachan, M. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:38762-38778, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) URL BibTeX

Empirical Inference Conference Paper Geometry-Aware Instrumental Variable Regression Kremer, H., Schölkopf, B. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:25560-25582, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) URL BibTeX

Empirical Inference Conference Paper Implicit meta-learning may lead language models to trust more reliable sources Krasheninnikov, D., Krasheninnikov, E., Mlodozeniec, B. K., Maharaj, T., Krueger, D. Proceedings of the 41st International Conference on Machine Learning, 235:25534-25559, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) URL BibTeX

Empirical Inference Conference Paper Improving Neural Additive Models with Bayesian Principles Bouchiat, K., Immer, A., Yèche, H., Rätsch, G., Fortuin, V. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:4416-4443, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) URL BibTeX

Empirical Inference Conference Paper On the Growth of Mistakes in Differentially Private Online Learning: A Lower Bound Perspective Dmitriev, D., Szabó, K., Sanyal, A. Proceedings of the 37th Annual Conference on Learning Theory (COLT), 247:1379-1398, Proceedings of Machine Learning Research, (Editors: Agrawal, Shipra and Roth, Aaron), PMLR, July 2024, (talk) (Published) URL BibTeX

Empirical Inference Robust Machine Learning Conference Paper Position: Understanding LLMs Requires More Than Statistical Generalization Reizinger, P., Ujváry, S., Mészáros, A., Kerekes, A., Brendel, W., Huszár, F. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:42365-42390, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) arXiv URL BibTeX

Empirical Inference Article Probabilistic pathway-based multimodal factor analysis Immer, A., Stark, S. G., Jacob, F., Bonilla, X., Thomas, T., Kahles, A., Goetze, S., Milani, E. S., Wollscheid, B., Consortium, T. T. P., et al. Bioinformatics, 40(Supplement 1):i189-i198, July 2024 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Products, Abstractions and Inclusions of Causal Spaces Buchholz, S., Park, J., Schölkopf, B. 40th Conference on Uncertainty in Artificial Intelligence (UAI), 244:430-449, Proceedings of Machine Learning Research, (Editors: Kiyavash, Negar and Mooij, Joris M.), PMLR, July 2024 (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Provable Privacy with Non-Private Pre-Processing Hu, Y., Sanyal, A., Schölkopf, B. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:19402-19437, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) URL BibTeX

Empirical Inference Conference Paper Robustness of Nonlinear Representation Learning Buchholz, S., Schölkopf, B. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:4785-4821, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) URL BibTeX

Empirical Inference Learning and Dynamical Systems Robotics Conference Paper Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion Guist, S., Schneider, J., Ma, H., Chen, L., Berenz, V., Martus, J., Ott, H., Grüninger, F., Muehlebach, M., Fiene, J., et al. Proceedings of Robotics: Science and Systems, July 2024 (Published) arXiv Project Page DOI URL BibTeX

Empirical Inference Conference Paper Simultaneous identification of models and parameters of scientific simulators Schröder, C., Macke, J. H. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:43895-43927, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) URL BibTeX

Empirical Inference Conference Paper Stitching Manifolds: Leveraging Interaction to Compose Object Representations into Scenes Keurti, H., Schölkopf, B., Aceituno, P. V., Grewe, B. ICML 2024 Workshop on Geometry-grounded Representation Learning and Generative Modeling (GRaM), July 2024 (Published) URL BibTeX

Empirical Inference Conference Paper Targeted Reduction of Causal Models Kekić, A., Schölkopf, B., Besserve, M. 40th Conference on Uncertainty in Artificial Intelligence (UAI), 244:1953-1980, Proceedings of Machine Learning Research, (Editors: Kiyavash, Negar and Mooij, Joris M.), PMLR, July 2024 (Published) arXiv URL BibTeX

Human Aspects of Machine Learning Empirical Inference Conference Paper The Role of Learning Algorithms in Collective Action Ben-Dov*, O., Fawkes*, J., Samadi, S., Sanyal, A. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:3443-3461, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024, *equal contribution (Published) URL BibTeX

Empirical Inference Conference Paper Unveiling CLIP Dynamics: Linear Mode Connectivity and Generalization Abdolahpourrostam, A., Sanyal, A., Moosavi-Dezfooli, S. ICML 2024 Workshop on Foundation Models in the Wild, July 2024 (Published) URL BibTeX

Empirical Inference Conference Paper What Makes Safety Fine-tuning Methods Safe? A Mechanistic Study Jain, S., Lubana, E. S., Oksuz, K., Joy, T., Torr, P. H. S., Sanyal, A., Dokania, P. K. ICML 2024 Workshop on Mechanistic Interpretability (Spotlight), July 2024 (Published) URL BibTeX

Empirical Inference Ph.D. Thesis Advancing Normalising Flows to Model Boltzmann Distributions Stimper, V. University of Cambridge, UK, Cambridge, June 2024, (Cambridge-Tübingen-Fellowship-Program) (Published) BibTeX

Empirical Inference Conference Paper Analyzing the Role of Semantic Representations in the Era of Large Language Models Jin*, Z., Chen*, Y., Gonzalez*, F., Liu, J., Zhang, J., Michael, J., Schölkopf, B., Diab, M. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Volume 1: Long Papers:3781-3798, (Editors: Duh, Kevin and Gomez, Helena and Bethard, Steven), Association for Computational Linguistics, June 2024, *equal contribution (Published) arXiv DOI URL BibTeX

Empirical Inference Conference Paper Automatic Generation of Model and Data Cards: A Step Towards Responsible AI Liu, J., Li, W., Jin, Z., Diab, M. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), Volume 1: Long Papers:1975-1997, (Editors: Duh, Kevin and Gomez, Helena and Bethard, Steven), Association for Computational Linguistics, June 2024 (Published) DOI URL BibTeX

Empirical Inference Conference Paper GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphs Gao, G., Liu, W., Chen, A., Geiger, A., Schölkopf, B. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 21295-21304, IEEE, CVPR, January 2024 (Published) DOI URL BibTeX

Empirical Inference Conference Paper Can Large Language Models Infer Causation from Correlation? Jin, Z., Liu, J., Lyu, Z., Poff, S., Sachan, M., Mihalcea, R., Diab*, M., Schölkopf*, B. The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal supervision (Published) arXiv URL BibTeX

Empirical Inference Conference Paper Causal Modeling with Stationary Diffusions Lorch, L., Krause*, A., Schölkopf*, B. Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 238:1927-1935, Proceedings of Machine Learning Research, (Editors: Dasgupta, Sanjoy and Mandt, Stephan and Li, Yingzhen), PMLR, May 2024, *equal supervision (Published) URL BibTeX

Empirical Inference Conference Paper Certified private data release for sparse Lipschitz functions Donhauser, K., Lokna, J., Sanyal, A., Boedihardjo, M., Hönig, R., Yang, F. Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 238:1396-1404, Proceedings of Machine Learning Research, (Editors: Dasgupta, Sanjoy and Mandt, Stephan and Li, Yingzhen), PMLR, May 2024 (Published) URL BibTeX

Empirical Inference Conference Paper Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding Pace, A., Yèche, H., Schölkopf, B., Rätsch, G., Tennenholtz, G. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX

Perceiving Systems Empirical Inference Conference Paper Ghost on the Shell: An Expressive Representation of General 3D Shapes Liu, Z., Feng, Y., Xiu, Y., Liu, W., Paull, L., Black, M. J., Schölkopf, B. In Proceedings of the Twelfth International Conference on Learning Representations (ICLR), The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) Home Code Video Project BibTeX

Empirical Inference Article Grundfragen der künstlichen Intelligenz Schölkopf, B. astronomie - Das Magazin, 42, May 2024 (Published) URL BibTeX

Empirical Inference Conference Paper Identifying Policy Gradient Subspaces Schneider, J., Schumacher, P., Guist, S., Chen, L., Häufle, D., Schölkopf, B., Büchler, D. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX

Empirical Inference Autonomous Learning Conference Paper Multi-View Causal Representation Learning with Partial Observability Yao, D., Xu, D., Lachapelle, S., Magliacane, S., Taslakian, P., Martius, G., von Kügelgen, J., Locatello, F. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX

Empirical Inference Conference Paper Open X-Embodiment: Robotic Learning Datasets and RT-X Models Open X-Embodiment Collaboration ( incl. Guist, S., Schneider, J., Schölkopf, B., Büchler, D. ). IEEE International Conference on Robotics and Automation (ICRA), 6892-6903, May 2024 (Published) arXiv DOI URL BibTeX

Empirical Inference Conference Paper Out-of-Variable Generalization for Discriminative Models Guo, S., Wildberger, J., Schölkopf, B. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX

Empirical Inference Perceiving Systems Conference Paper Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization Liu, W., Qiu, Z., Feng, Y., Xiu, Y., Xue, Y., Yu, L., Feng, H., Liu, Z., Heo, J., Peng, S., et al. In Proceedings of the Twelfth International Conference on Learning Representations (ICLR), The Twelfth International Conference on Learning Representations, May 2024 (Published) Home Code HuggingFace project URL BibTeX

Empirical Inference Conference Paper Skill or Luck? Return Decomposition via Advantage Functions Pan, H., Schölkopf, B. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX

Empirical Inference Conference Paper Some Intriguing Aspects about Lipschitz Continuity of Neural Networks Khromov*, G., Singh*, S. P. The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (Published) arXiv BibTeX

Empirical Inference Conference Paper Stochastic Gradient Descent for Gaussian Processes Done Right Lin*, J. A., Padhy*, S., Antorán*, J., Tripp, A., Terenin, A., Szepesvari, C., Hernández-Lobato, J. M., Janz, D. The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (Published) arXiv BibTeX

Empirical Inference Conference Paper Targeted Reduction of Causal Models Kekić, A., Schölkopf, B., Besserve, M. ICLR 2024 Workshop on AI4DifferentialEquations In Science, May 2024 (Published) URL BibTeX

Empirical Inference Autonomous Learning Conference Paper The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks Spieler, A., Rahaman, N., Martius, G., Schölkopf, B., Levina, A. In The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX

Empirical Inference Conference Paper Towards Meta-Pruning via Optimal Transport Theus, A., Geimer, O., Wicke, F., Hofmann, T., Anagnostidis, S., Singh, S. P. The Twelfth International Conference on Learning Representations (ICLR), May 2024 (Published) arXiv BibTeX

Empirical Inference Conference Paper Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion Meterez*, A., Joudaki*, A., Orabona, F., Immer, A., Rätsch, G., Daneshmand, H. The Twelfth International Conference on Learning Representations (ICLR), May 2024, *equal contribution (Published) arXiv BibTeX